Depending on the application domain, the idea of spectral decomposition can be applied to either partitioning or clustering. The fundamental difference between them is the fact that in partitioning scenarios tightly balanced partitions are favored [1]}, and are possibly enforced using additional constraints, while in clustering the focus is on identifying the existence of communities [2]} that are not necessarily of equal size.
